Can CMIP5 models replicate long-term variability of storm characteristics in the WNP? James Bramante

The Western North Pacific Figure taken from Laing and Evans (2011). Introduction to Tropical Meteorology. University Corporation for Atmospheric Research: Boulder, CO.

Shift in storm frequency/location Figures reproduced and modified with permission from Woodruff et al. (2015). “Depositional evidence for Kamikaze typhoons and links to changes in typhoon climatology.” Geology 43: 91-94.

Characterizing tropical cyclones in GCMs Three main methods: Direct, fully-coupled simulation Requires high resolution Most computationally costly Dynamic downscaling Regionally-specific modeling using GCM output as boundary conditions Less computationally costly Genesis Potential Indices Least computationally costly Can be calculated from monthly means, and is robust both globally and within ocean basins

Genesis Potential Index (GPI) Introduced by Kerry Emanuel in 2004 and updated in 2008: η = Low-level ambient vorticity required for storm initiation χ = Saturation deficit. Obstacle to storm intensification. PI = Potential intensity = the maximum possible strength of a storm after intensification. A function of potential energy from convection and temperature gradients. Vshear = vertical shear of horizontal winds. Disrupts convection and storm intensification.

Aim: To test CMIP5 performance over LM with respect to storms Do CMIP5 models replicate storm seasonal and interannual variability in Historical period, and is variability unchanged from LM? Do they replicate the shift in storm genesis frequency and location found in WNP storm records ~500 yr BP?

CMIP5 in the Last Millennium experiment

Seasonal variability Model replication of seasonality surprisingly good Cycle amplitude also replicated well

Seasonal variability (cont.) GPI and vorticity seasonality not as well replicated

Interannual variability (ENSO)

Interannual variability (ENSO) (cont.) Historical Last Millennium

Aim: To test CMIP5 performance over LM with respect to storms Do CMIP5 models replicate storm seasonal and inter-annual variability in Historical period, and is variability unchanged from LM? Yes to inter-annual/spatial. Seasonal not replicated as well, but probably okay if averaging over JJA/JASON. Do they replicate the shift in storm genesis frequency and location found in WNP storm records ~500 yr BP?

Aim: To test CMIP5 performance over LM with respect to storms Do CMIP5 models replicate storm seasonal and inter-annual variability in Historical period, and is variability unchanged from LM? Yes to inter-annual/spatial. Seasonal not replicated as well, but probably okay if averaging over JJA/JASON. Do they replicate the shift in storm genesis frequency and location found in WNP storm records ~500 yr BP?

CMIP5 shifts in storm magnitude/track over LM

Aim: To test CMIP5 performance over LM with respect to storms Do CMIP5 models replicate storm seasonal and inter-annual variability in Historical period, and is variability unchanged from LM? Yes to inter-annual/spatial. Seasonal not replicated as well, but probably okay if averaging over JJA/JASON. Do they replicate the shift in storm genesis frequency and location found in WNP storm records ~500 yr BP? Surprisingly, they do indicate a southwards shift in storm track caused by stronger shear to the north. Also, magnitude decreases over Japan.

While I was performing my analysis… Yan et al. (2016). “Variations in large‑scale tropical cyclone genesis factors over the western North Pacific in the PMIP3 last millennium simulations.” Climate Dynamics doi:10.1007/s00382-016-3120-9 MCA LIA Vertical shear percent difference from all of LM run.

Further: Vertical shear seasonality NCEP GCM Historical

Shear: Little Ice Age v. Medieval Climate Anomaly

Recap CMIP5 models replicate seasonal and ENSO-related variability in storm genesis in the WNP pretty well CMIP5 models replicate sediment-proxy derived shift in storm tracks and magnitude from Japan to southern China, but modeled shift is small Seasonal anomalies in vertical shear give strongest explanation for shift in storm tracks In this case, vertical shear spatial anomalies likely controlled by subtropical ridge